Probabilistic Fatigue/Creep Optimization of Turbine Bladed Disk with Fuzzy Multi-Extremum Response Surface Method

Area of Science:

• Mechanical Engineering
• Materials Science
• Reliability Engineering

Background:

• Turbine bladed disks are critical components susceptible to fatigue and creep failures.
• Optimizing these structures requires advanced methods to account for probabilistic factors and multi-failure modes.
• Existing methods like Monte Carlo simulation can be computationally intensive.

Purpose of the Study:

• To develop and apply a novel fuzzy multi-extremum response surface method (FMERSM) for probabilistic fatigue/creep coupling optimization.
• To comprehensively optimize multi-component structures with multiple failure modes.
• To enhance the reliability and lifespan of turbine bladed disks.

Main Methods:

• Development of the fuzzy multi-extremum response surface method (FMERSM) integrating extremum response surface method, hierarchical strategy, and fuzzy theory.
• Modeling FMERSM and evaluating fatigue/creep damage in turbine bladed disks.
• Implementing fuzzy probabilistic fatigue/creep optimization using rotor speed, temperature, and density as parameters.

Main Results:

• Identified gas temperature (T) and rotor speed (ω) as critical control parameters for bladed disk optimization.
• Achieved significant reductions in T (85 K) and ω (113 rad/s) post-optimization.
• Demonstrated higher modeling accuracy and computational efficiency compared to the Monte Carlo method (MCM).

Conclusions:

• The FMERSM provides an effective approach for probabilistic multi-failure optimization of complex structures.
• Optimized parameters significantly extend bladed disk life and reduce failure damages.
• This research contributes to mechanical reliability theory and offers a new tool for component optimization.